Various types of devices for automated optical inspection of electrical circuits are known. Typically one or more gray level images of an electrical circuit under inspection are acquired. In some conventional devices for automated optical inspection of electrical circuits a binary representation of the electrical circuit, generated from a gray level image of the electrical circuit, is employed for at least some inspection operations. In some automated optical inspection applications the binary representation of an electrical circuit under inspection has a spatial resolution which is higher than the spatial resolution of the gray level image.
The PC Micro II™ and Inspire™ 9060 automated optical inspection systems, available from Orbotech Ltd. of Israel, are representative of conventional automated optical inspection systems for inspecting electrical circuits. In these conventional systems a gray level image of an electrical circuit under inspection is acquired. In a first channel the gray level image is convolved with a function approximating the Laplacian of a Gaussian function. In a second channel a threshold is applied to pixels in the same gray level image to determine which pixels in the image are representative of either conductor or substrate, to a high degree of confidence. The output of the second channel is applied to the output of the convolved image from the first channel to modify the convolved image. The locations of zero-crossings between oppositely signed pixels in the modified convolved image are calculated, and the zero-crossings subsequently are employed to generate an improved resolution binary image of an electrical circuit being inspected.
In other conventional devices for automated optical inspection of electrical circuits a contour representation of the electrical circuit, generated from the gray level image of the electrical circuit is employed for at least some inspection operations. Contours are an approximation of the location of the transition between regions exhibiting optically distinguishable characteristics, for example between conductor and substrate in an electrical circuit.
Additionally, color image acquisition systems recently have been employed in the automated optical inspection of electrical circuits.
The following reference describes edge detection methods:
D. Marr and E. Hildreth, Theory of Edge Detection, Proceedings of the Royal Society of London.
The following references describe color image processing methods:
M. Chapron, “A New Chromatic Edge-Detector Used for Color Image Segmentation”, 11th APR International Conference on Pattern Recognition, Vol. III. IEEE Computer Society Press, Los Alamitos, Calif., USA, 1992.
Philippe Pujas and Marie-Jose Aldon, “Robust Colour Image Segmentation”, 7th International Conference on Advanced Robotics, San Filiu de Guixols, Spain, Sep. 22, 1995, and
Leila Shararenko, Maria Petrou, and Josef Kittler, “Automatic Watershed Segmentation of Randomly Textured Colour Images, IEEE Transactions on Image Processing, Vol. 6, no. 11, 1997.
The following U.S. patent application and published PCT patent application describe color image processing methods:
U.S. Pat. No. 5,483,603 and WO 00/11454
The following U.S. patents and published PCT patent application describe techniques employed in automated optical inspection of electrical circuits:
U.S. Pat. No. 5,774,572, U.S. Pat. No. 5,774,573, U.S. Pat. No. 5,586,058, U.S. Pat. No. 5,619,429, WO 00/19372 and U.S. Pat. No. 6,175,645.